Improved Classification Rates for Localized Algorithms under Margin Conditions

Language: English

Published by Springer VS, 2020

3658295902 / 9783658295905

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - Support vector machines (SVMs) are one of the most successful algorithms on small and medium-sized data sets, but on large-scale data sets their training and predictions become computationally infeasible. The author considers a spatially defined data chunking method for large-scale learning problems, leading to so-called localized SVMs, and implements an in-depth mathematical analysis with theoretical guarantees, which in particular include classification rates. The statistical analysis relies on a new and simple partitioning based technique and takes well-known margin conditions into account that describe the behavior of the data-generating distribution. It turns out that the rates outperform known rates of several other learning algorithms under suitable sets of assumptions. From a practical point of view, the author shows that a common training and validation procedure achieves the theoretical rates adaptively, that is, without knowing the margin parameters in advance.…

Seller Inventory # 9783658295905

Title
Improved Classification Rates for Localized Algorithms under Margin Conditions
Author
Ingrid Karin Blaschzyk
Publisher
Springer VS
Publication year
2020
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3658295902
ISBN 13
9783658295905
Item weight
197 grams
Dimensions
210x148x9 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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